Consistent and scalable monitoring of birds and habitats along a coffee production intensity gradient

Le résumé fourni par la source

Abstract Land use change associated with agricultural intensification is a leading driver of biodiversity loss in the tropics. To evaluate the habitat-biodiversity relationship in production systems of tropical agricultural commodities, which is critical for certifying and examining the success of biodiversity-friendly agricultural practices, birds are commonly used as indicators. However, consistently and reliably monitoring how bird communities are affected by land use change throughout the annual cycle in a way that can be scalable is challenging using traditional survey methods. In this study, we examined whether the automated analysis of audio data collected by passive acoustic monitoring, together with the analysis of remote sensing data, can be used to efficiently monitor avian biodiversity along the gradient of habitat degradation associated with the intensification of coffee production. Coffee is an important crop produced in tropical forested regions, whose production is expanding and intensifying, and coffee production systems form a gradient of ecological complexity ranging from forest-like shaded polyculture to dense sun-exposed monoculture. We used LiDAR technology to survey the habitat, in combination with autonomous recording units and a vocalisation classification algorithm to assess bird community composition in a coffee landscape comprising a shade-grown coffee farm, a sun coffee farm, and a forest remnant, located in southern Mexico. We found that combining LiDAR with the automated analysis of continuously collected bioacoustics data can capture the expected functional signatures of avian communities as a function of habitat quality in the coffee landscape. Thus, we show that this approach can be a robust way to monitor how biodiversity responds to land use intensification in the tropics. A major advantage of this approach is that it has the potential to be deployed cost-effectively at large scales to help design and certify biodiversity-friendly productive landscapes.

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